TRI-ML/dd3d
DD3D is a PyTorch implementation of a monocular 3D object detection model published at ICCV 2021.
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This repository contains the official PyTorch implementation of DD3D, a deep learning approach for monocular 3D object detection that estimates 3D bounding boxes from single camera images. The project includes training pipelines, model architectures, and evaluation code for the KITTI dataset. It uses Docker for environment reproducibility and integrates with Weights & Biases for experiment tracking.
Frequently asked
- What is TRI-ML/dd3d?
- DD3D is a PyTorch implementation of a monocular 3D object detection model published at ICCV 2021.
- Is dd3d open source?
- Yes — TRI-ML/dd3d is open source, released under the MIT license.
- What language is dd3d written in?
- TRI-ML/dd3d is primarily written in Python.
- How popular is dd3d?
- TRI-ML/dd3d has 493 stars on GitHub.
- Where can I find dd3d?
- TRI-ML/dd3d is on GitHub at https://github.com/TRI-ML/dd3d.